Artifical intelligence training method for identifying incorrect training data and artifical intelligence correcting method using the same

Abstract

The disclosure describes an artificial intelligence training method for identifying incorrect training data and an artificial intelligence correcting method using the same. When training an artificial intelligence (AI) model, a plurality of training data along with their corresponding tag data and coded data are input, thereby ensuring that the training process of the AI model remains unaffected. When the AI model is used to obtain an incorrect answer, the tag data are obtained based on the coded data. A piece of training data referenced by the incorrect answer is identified using the tag data, thereby efficiently updating the original incorrect training data.

What is claimed is: 
     
         1 . An artificial intelligence training method for identifying incorrect training data, comprising:
 Step (A): obtaining a plurality of training data and a plurality of tag data corresponding thereto;   Step (B): performing a coding process to convert the plurality of tag data into a plurality of coded data;   Step (C): inputting training data that include the plurality of training data and the plurality of coded data corresponding thereto to an original artificial intelligence (AI) model to obtain a trained artificial intelligence (AI) model; and   Step (D): testing the trained AI model to determine whether the trained AI model provides a correct answer and a piece of coded data, wherein the piece of coded data corresponds to a piece of training data referenced by the correct answer.   
     
     
         2 . The artificial intelligence training method for identifying incorrect training data according to  claim 1 , wherein each of the plurality of training data includes question data and answer data. 
     
     
         3 . The artificial intelligence training method for identifying incorrect training data according to  claim 1 , wherein the coding process is performed to convert the plurality of tag data into the plurality of coded data that are not understood by the original AI model. 
     
     
         4 . The artificial intelligence training method for identifying incorrect training data according to  claim 3 , wherein the coding process is performed to convert the plurality of tag data into the plurality of coded data that are composed of English letters, numbers, and symbols. 
     
     
         5 . The artificial intelligence training method for identifying incorrect training data according to  claim 1 , wherein the coding process is a Base 64  coding process. 
     
     
         6 . An artificial intelligence correcting method for identifying incorrect training data, comprising:
 Step (A): querying a trained artificial intelligence (AI) model to obtain an incorrect answer and a piece of coded data, wherein the piece of coded data corresponds to a piece of training data referenced by the incorrect answer;   Step (B): correcting the piece of training data into a piece of updated training data that corresponds to the piece of coded data;   Step (C): inputting training data that include the piece of updated training data and the piece of coded data to the AI model to obtain an updated artificial intelligence (AI) model; and   Step (D): testing the updated AI model to determine whether the updated AI model passes an enhanced scoring process.   
     
     
         7 . The artificial intelligence correcting method for identifying incorrect training data according to  claim 6 , wherein a decoding process is performed on the piece of coding data to obtain tag data and the piece of training data is queried based on the tag data. 
     
     
         8 . The artificial intelligence correcting method for identifying incorrect training data according to  claim 7 , wherein the decoding process is a Base64 decoding process. 
     
     
         9 . The artificial intelligence correcting method for identifying incorrect training data according to  claim 6 , wherein in the enhanced scoring process, a plurality of questions are provided to test the updated AI model, and the plurality of questions are associated with the piece of training data referenced by the incorrect data. 
     
     
         10 . The artificial intelligence correcting method for identifying incorrect training data according to  claim 6 , wherein in the enhanced scoring process, a plurality of keywords are provided based on the piece of training data referenced by the incorrect answer, and the plurality of keywords are configured to design the plurality of questions associated with the incorrect answer.